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Completed STUDENTSHIP UKRI Gateway to Research

Decentralised learning and networked communication in large populations of AI decision makers


Funder Engineering and Physical Sciences Research Council
Recipient Organization University of Oxford
Country United Kingdom
Start Date Sep 30, 2021
End Date Sep 29, 2025
Duration 1,460 days
Number of Grantees 2
Roles Student; Supervisor
Data Source UKRI Gateway to Research
Grant ID 2577365
Grant Description

Brief description of the context of the research including potential impact

Systems of numerous interacting autonomous decision makers ('agents') are likely to play an increasing role in many areas of our society, economy and infrastructure, with potential benefits for disaster response, financial markets, smart cities and energy grids, environmental monitoring and other cyber-physical systems. However, there is an explosion in computational complexity as the population size increases, making them difficult to scale for real-world usage. 'Mean-Field Games' (MFGs) are an area of game theory related to statistical physics, which can be combined with machine learning to address the scalability issue.

Nevertheless, methods for solving MFGs have traditionally relied on idealised assumptions that are unrealistic in practice. Aims and Objectives

I wish to bridge the gap between the abstract theory of MFGs and their practical usage in real-world problems. In particular, I am introducing inter-agent communication into the framework, to remove the reliance of theoretical techniques on the existence of a single controller that `puppeteers' all the agents. This can bring benefits in terms of robustness, flexibility and speed of convergence.

Novelty of the research methodology

MFGs remain a relatively underexplored area, especially with regards to the desiderata we may have for complex systems to be trained and deployed in the real world, such as decentralised learning. My introduction of inter-agent communication to the MFG framework is a novel contribution.

Alignment to EPSRC's strategies and research areas (which EPSRC research area the project relates to) Further information on the areas can be found on http://www.epsrc.ac.uk/research/ourportfolio/researchareas/

Research into large multi-agent systems is at the heart of several EPSRC research areas, including 'AI technologies', 'control engineering' and 'verification and correctness', with potential application to the likes of 'ICT networks and distributed systems' and 'infrastructure and urban systems'. Any companies or collaborators involved

None currently.

All Grantees

University of Oxford

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